Literature DB >> 9258528

A new approach to tracking of subjects at risk for hypercholesteremia over a period of 15 years: The Amsterdam Growth and Health Study.

J W Twisk1, H C Kemper, G J Mellenbergh, W van Mechelen.   

Abstract

Because 'traditional' tracking analyses have some drawbacks, this paper presents a new method, which is based on generalized estimating equations (GEE). The new method is illustrated with data from the Amsterdam Growth and Health Study. In this observational longitudinal study six repeated measurements were carried out on 181 subjects (initial age 13 years) over a period of 15 years. Tracking was assessed for total cholesterol (TC), high density lipoprotein (HDL) and the TC/HDL ratio by calculating the odds ratio (OR) for subjects at risk at the age of 13 years regarding the development of their risk status over a 15 year period. These ORs can be interpreted as tracking coefficients. Three methods were compared: percentage of subjects who maintain their position in a certain risk group (i.e. univariate logistic regression), multivariate logistic regression and GEE. The three methods differ in the possibility of using all available data in the analysis and in the possibility of adjusting for certain covariates. Based on this, the GEE-approach seemed to be the most appropriate to calculate tracking coefficients for subjects at risk. When the risk groups were defined according to objective (absolute) risk values, for TC the GEE-OR was 10.1 (95% confidence interval (CI) 5.0-21.9), for HDL 14.4 (95% CI 7.2-28.7) and for the TC/HDL ratio 25.5 (95% CI 11.5-56.8). It can be concluded that the GEE-approach is very suitable to assess tracking for subjects at risk.

Entities:  

Mesh:

Substances:

Year:  1997        PMID: 9258528     DOI: 10.1023/a:1007373705865

Source DB:  PubMed          Journal:  Eur J Epidemiol        ISSN: 0393-2990            Impact factor:   8.082


  19 in total

1.  A simplified method for the estimation of total cholesterol in serum and demonstration of its specificity.

Authors:  L L ABEL; B B LEVY; B B BRODIE; F E KENDALL
Journal:  J Biol Chem       Date:  1952-03       Impact factor: 5.157

2.  Longitudinal data analysis for discrete and continuous outcomes.

Authors:  S L Zeger; K Y Liang
Journal:  Biometrics       Date:  1986-03       Impact factor: 2.571

3.  Longitudinal development of lipoprotein levels in males and females aged 12-28 years: the Amsterdam Growth and Health Study.

Authors:  J W Twisk; H C Kemper; G J Mellenbergh
Journal:  Int J Epidemiol       Date:  1995-02       Impact factor: 7.196

4.  Mathematical and analytical aspects of tracking.

Authors:  J W Twisk; H C Kemper; G J Mellenbergh
Journal:  Epidemiol Rev       Date:  1994       Impact factor: 6.222

5.  Factors influencing tracking of cholesterol and high-density lipoprotein: the Amsterdam Growth and Health Study.

Authors:  J W Twisk; H C Kemper; D J Mellenbergh; W van Mechelen
Journal:  Prev Med       Date:  1996 May-Jun       Impact factor: 4.018

6.  Changes in and stability of cardiovascular responses to behavioral stress: results from a four-year longitudinal study of children.

Authors:  K A Matthews; K L Woodall; C M Stoney
Journal:  Child Dev       Date:  1990-08

7.  Tracking of serum lipids and lipoproteins in children over an 8-year period: the Bogalusa Heart Study.

Authors:  D S Freedman; C L Shear; S R Srinivasan; L S Webber; G S Berenson
Journal:  Prev Med       Date:  1985-03       Impact factor: 4.018

8.  Tracking of serum HDL-cholesterol and other lipids in children and adolescents: the Cardiovascular Risk in Young Finns Study.

Authors:  K V Porkka; J S Viikari; H K Akerblom
Journal:  Prev Med       Date:  1991-11       Impact factor: 4.018

9.  Tracking of blood lipids and blood pressures in school age children: the Muscatine study.

Authors:  W R Clarke; H G Schrott; P E Leaverton; W E Connor; R M Lauer
Journal:  Circulation       Date:  1978-10       Impact factor: 29.690

10.  Dynamic changes of serum lipoproteins in children during adolescence and sexual maturation.

Authors:  G S Berenson; S R Srinivasan; J L Cresanta; T A Foster; L S Webber
Journal:  Am J Epidemiol       Date:  1981-02       Impact factor: 4.897

View more
  1 in total

1.  Inflammation markers are associated with cardiovascular diseases risk in adolescents: the Young Hearts project 2000.

Authors:  Nienke J Wijnstok; Jos W R Twisk; Ian S Young; Jayne V Woodside; Cheryl McFarlane; Jane McEneny; Trynke Hoekstra; Liam Murray; Colin A G Boreham
Journal:  J Adolesc Health       Date:  2010-05-20       Impact factor: 7.830

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.